Volunteer Summary

Table

Text

sets

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sets with group and time_point (formula: sets ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.62) and the part related to the fixed effects alone (marginal R2) is of 0.05. The model’s intercept, corresponding to group = control and time_point = 1st, is at 18.67 (95% CI [17.91, 19.42], t(152) = 48.59, p < .001). Within this model:

• The effect of group [treatment] is statistically significant and positive (beta = 1.21, 95% CI [0.07, 2.34], t(152) = 2.09, p = 0.037; Std. beta = 0.45, 95% CI [0.03, 0.88])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.09, 95% CI [-0.89, 0.71], t(152) = -0.22, p = 0.828; Std. beta = -0.03, 95% CI [-0.33, 0.27])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.02, 95% CI [-1.13, 1.17], t(152) = 0.04, p = 0.969; Std. beta = 8.66e-03, 95% CI [-0.42, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

setv

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict setv with group and time_point (formula: setv ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.69) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.86 (95% CI [10.32, 11.40], t(152) = 39.31, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.56, 95% CI [-0.25, 1.38], t(152) = 1.35, p = 0.177; Std. beta = 0.29, 95% CI [-0.13, 0.72])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.33, 95% CI [-0.19, 0.85], t(152) = 1.25, p = 0.210; Std. beta = 0.17, 95% CI [-0.10, 0.44])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.18, 95% CI [-0.92, 0.56], t(152) = -0.47, p = 0.639; Std. beta = -0.09, 95% CI [-0.48, 0.29])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

maks

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict maks with group and time_point (formula: maks ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.72) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 44.38 (95% CI [43.29, 45.47], t(151) = 79.80, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.07, 95% CI [-0.57, 2.71], t(151) = 1.28, p = 0.200; Std. beta = 0.27, 95% CI [-0.14, 0.69])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.95, 1.01], t(151) = 0.06, p = 0.953; Std. beta = 7.50e-03, 95% CI [-0.24, 0.26])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.09, 95% CI [-1.50, 1.32], t(151) = -0.13, p = 0.900; Std. beta = -0.02, 95% CI [-0.38, 0.34])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ibs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ibs with group and time_point (formula: ibs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.75) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.33 (95% CI [14.63, 16.03], t(152) = 42.85, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.37, 95% CI [-0.69, 1.42], t(152) = 0.68, p = 0.497; Std. beta = 0.15, 95% CI [-0.28, 0.58])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.26, 95% CI [-0.35, 0.86], t(152) = 0.84, p = 0.403; Std. beta = 0.10, 95% CI [-0.14, 0.35])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.34, 95% CI [-0.52, 1.20], t(152) = 0.77, p = 0.440; Std. beta = 0.14, 95% CI [-0.21, 0.49])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_e

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_e with group and time_point (formula: ers_e ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.80) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.98 (95% CI [11.47, 12.49], t(152) = 45.69, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.29, 95% CI [-0.48, 1.07], t(152) = 0.74, p = 0.456; Std. beta = 0.17, 95% CI [-0.28, 0.61])
• The effect of time point [2nd] is statistically significant and negative (beta = -0.46, 95% CI [-0.86, -0.06], t(152) = -2.25, p = 0.025; Std. beta = -0.26, 95% CI [-0.49, -0.03])
• The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 0.66, 95% CI [0.09, 1.23], t(152) = 2.25, p = 0.024; Std. beta = 0.38, 95% CI [0.05, 0.70])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ers_r

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ers_r with group and time_point (formula: ers_r ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.59) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.98 (95% CI [10.50, 11.46], t(152) = 44.89, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.49, 95% CI [-0.23, 1.22], t(152) = 1.34, p = 0.180; Std. beta = 0.29, 95% CI [-0.14, 0.72])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.49, 0.55], t(152) = 0.11, p = 0.910; Std. beta = 0.02, 95% CI [-0.29, 0.32])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.03, 95% CI [-0.71, 0.78], t(152) = 0.09, p = 0.926; Std. beta = 0.02, 95% CI [-0.42, 0.46])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_pa

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_pa with group and time_point (formula: pss_pa ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.68) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 43.82 (95% CI [42.14, 45.51], t(152) = 51.05, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.70, 95% CI [-0.84, 4.24], t(152) = 1.31, p = 0.189; Std. beta = 0.29, 95% CI [-0.14, 0.73])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -1.24, 95% CI [-2.87, 0.40], t(152) = -1.48, p = 0.138; Std. beta = -0.21, 95% CI [-0.50, 0.07])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.18, 95% CI [-2.16, 2.53], t(152) = 0.15, p = 0.879; Std. beta = 0.03, 95% CI [-0.37, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss_ps

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss_ps with group and time_point (formula: pss_ps ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 25.76 (95% CI [23.69, 27.84], t(152) = 24.31, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -1.26, 95% CI [-4.40, 1.87], t(152) = -0.79, p = 0.429; Std. beta = -0.17, 95% CI [-0.58, 0.25])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 1.53, 95% CI [-0.68, 3.75], t(152) = 1.35, p = 0.176; Std. beta = 0.20, 95% CI [-0.09, 0.50])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.52, 95% CI [-4.71, 1.67], t(152) = -0.93, p = 0.350; Std. beta = -0.20, 95% CI [-0.62, 0.22])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

pss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict pss with group and time_point (formula: pss ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.64) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 43.71 (95% CI [40.54, 46.87], t(152) = 27.05, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -1.73, 95% CI [-6.51, 3.05], t(152) = -0.71, p = 0.478; Std. beta = -0.15, 95% CI [-0.57, 0.26])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 3.18, 95% CI [-0.05, 6.40], t(152) = 1.93, p = 0.053; Std. beta = 0.28, 95% CI [-4.11e-03, 0.56])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -2.09, 95% CI [-6.73, 2.54], t(152) = -0.89, p = 0.376; Std. beta = -0.18, 95% CI [-0.58, 0.22])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_responsible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_responsible with group and time_point (formula: rki_responsible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.66) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.45 (95% CI [19.25, 21.65], t(152) = 33.33, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 1.25, 95% CI [-0.56, 3.06], t(152) = 1.35, p = 0.177; Std. beta = 0.30, 95% CI [-0.13, 0.72])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.12, 95% CI [-1.06, 1.31], t(152) = 0.20, p = 0.839; Std. beta = 0.03, 95% CI [-0.25, 0.31])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.58, 95% CI [-2.28, 1.12], t(152) = -0.67, p = 0.504; Std. beta = -0.14, 95% CI [-0.54, 0.27])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_nonlinear

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_nonlinear with group and time_point (formula: rki_nonlinear ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.92 (95% CI [12.05, 13.79], t(152) = 29.18, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.75, 95% CI [-0.56, 2.06], t(152) = 1.13, p = 0.259; Std. beta = 0.24, 95% CI [-0.18, 0.67])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.23, 95% CI [-1.13, 0.66], t(152) = -0.51, p = 0.609; Std. beta = -0.08, 95% CI [-0.37, 0.21])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.45, 95% CI [-0.84, 1.73], t(152) = 0.68, p = 0.498; Std. beta = 0.14, 95% CI [-0.27, 0.56])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_peer

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_peer with group and time_point (formula: rki_peer ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.69) and the part related to the fixed effects alone (marginal R2) is of 4.40e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 20.08 (95% CI [19.27, 20.89], t(152) = 48.74, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.30, 95% CI [-0.92, 1.51], t(152) = 0.48, p = 0.633; Std. beta = 0.11, 95% CI [-0.33, 0.55])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.10, 95% CI [-0.66, 0.86], t(152) = 0.26, p = 0.795; Std. beta = 0.04, 95% CI [-0.24, 0.31])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.12, 95% CI [-0.98, 1.21], t(152) = 0.21, p = 0.834; Std. beta = 0.04, 95% CI [-0.35, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki_expect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki_expect with group and time_point (formula: rki_expect ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.40) and the part related to the fixed effects alone (marginal R2) is of 0.07. The model’s intercept, corresponding to group = control and time_point = 1st, is at 4.39 (95% CI [4.10, 4.69], t(152) = 29.25, p < .001). Within this model:

• The effect of group [treatment] is statistically significant and positive (beta = 0.53, 95% CI [0.09, 0.98], t(152) = 2.35, p = 0.019; Std. beta = 0.49, 95% CI [0.08, 0.90])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.21, 95% CI [-0.18, 0.59], t(152) = 1.06, p = 0.291; Std. beta = 0.19, 95% CI [-0.16, 0.55])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.01, 95% CI [-0.57, 0.54], t(152) = -0.05, p = 0.959; Std. beta = -0.01, 95% CI [-0.53, 0.50])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

rki

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict rki with group and time_point (formula: rki ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.77) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 57.84 (95% CI [55.60, 60.09], t(152) = 50.52, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 2.83, 95% CI [-0.55, 6.22], t(152) = 1.64, p = 0.101; Std. beta = 0.38, 95% CI [-0.07, 0.83])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 3.07e-03, 95% CI [-1.83, 1.84], t(152) = 3.28e-03, p = 0.997; Std. beta = 4.11e-04, 95% CI [-0.25, 0.25])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.27, 95% CI [-2.36, 2.90], t(152) = 0.20, p = 0.840; Std. beta = 0.04, 95% CI [-0.32, 0.39])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_possible

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_possible with group and time_point (formula: raq_possible ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.65) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.31 (95% CI [14.69, 15.93], t(152) = 48.45, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.21, 95% CI [-0.72, 1.15], t(152) = 0.44, p = 0.658; Std. beta = 0.10, 95% CI [-0.34, 0.53])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.20, 95% CI [-0.82, 0.42], t(152) = -0.63, p = 0.528; Std. beta = -0.09, 95% CI [-0.38, 0.20])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.61, 95% CI [-0.28, 1.51], t(152) = 1.34, p = 0.179; Std. beta = 0.28, 95% CI [-0.13, 0.70])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq_difficulty

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq_difficulty with group and time_point (formula: raq_difficulty ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 1.66e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.22 (95% CI [11.72, 12.72], t(152) = 47.89, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.04, 95% CI [-0.79, 0.71], t(152) = -0.11, p = 0.916; Std. beta = -0.02, 95% CI [-0.46, 0.42])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.06, 95% CI [-0.40, 0.52], t(152) = 0.26, p = 0.794; Std. beta = 0.04, 95% CI [-0.23, 0.30])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.14, 95% CI [-0.51, 0.80], t(152) = 0.43, p = 0.667; Std. beta = 0.08, 95% CI [-0.30, 0.47])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

raq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict raq with group and time_point (formula: raq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.75) and the part related to the fixed effects alone (marginal R2) is of 7.13e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 27.53 (95% CI [26.45, 28.61], t(152) = 49.99, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.17, 95% CI [-1.46, 1.80], t(152) = 0.21, p = 0.837; Std. beta = 0.05, 95% CI [-0.40, 0.49])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.15, 95% CI [-1.08, 0.77], t(152) = -0.32, p = 0.746; Std. beta = -0.04, 95% CI [-0.29, 0.21])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.77, 95% CI [-0.56, 2.09], t(152) = 1.13, p = 0.258; Std. beta = 0.21, 95% CI [-0.15, 0.57])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

who

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict who with group and time_point (formula: who ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.69) and the part related to the fixed effects alone (marginal R2) is of 6.71e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.76 (95% CI [13.52, 16.01], t(152) = 23.19, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.26, 95% CI [-1.62, 2.14], t(152) = 0.27, p = 0.786; Std. beta = 0.06, 95% CI [-0.36, 0.48])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.26, 95% CI [-1.43, 0.90], t(152) = -0.44, p = 0.657; Std. beta = -0.06, 95% CI [-0.32, 0.20])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.82, 95% CI [-0.86, 2.49], t(152) = 0.96, p = 0.338; Std. beta = 0.18, 95% CI [-0.19, 0.56])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

phq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict phq with group and time_point (formula: phq ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.80) and the part related to the fixed effects alone (marginal R2) is of 5.10e-04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.29 (95% CI [2.34, 4.25], t(152) = 6.75, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.16, 95% CI [-1.29, 1.60], t(152) = 0.21, p = 0.832; Std. beta = 0.04, 95% CI [-0.37, 0.46])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.15, 95% CI [-0.59, 0.89], t(152) = 0.40, p = 0.690; Std. beta = 0.04, 95% CI [-0.17, 0.25])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.11, 95% CI [-1.17, 0.94], t(152) = -0.21, p = 0.831; Std. beta = -0.03, 95% CI [-0.34, 0.27])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

gad

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict gad with group and time_point (formula: gad ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 2.57e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 2.90 (95% CI [2.06, 3.75], t(152) = 6.72, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -0.08, 95% CI [-1.35, 1.20], t(152) = -0.12, p = 0.906; Std. beta = -0.02, 95% CI [-0.44, 0.39])
• The effect of time point [2nd] is statistically non-significant and positive (beta = 0.35, 95% CI [-0.47, 1.17], t(152) = 0.85, p = 0.398; Std. beta = 0.11, 95% CI [-0.15, 0.38])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.20, 95% CI [-1.38, 0.97], t(152) = -0.34, p = 0.734; Std. beta = -0.07, 95% CI [-0.45, 0.31])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_pcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_pcs with group and time_point (formula: nb_pcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.74) and the part related to the fixed effects alone (marginal R2) is of 7.67e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 51.92 (95% CI [49.87, 53.97], t(151) = 49.63, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and negative (beta = -1.72, 95% CI [-4.80, 1.35], t(151) = -1.10, p = 0.272; Std. beta = -0.23, 95% CI [-0.65, 0.18])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.76, 95% CI [-2.52, 1.01], t(151) = -0.84, p = 0.402; Std. beta = -0.10, 95% CI [-0.34, 0.14])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.74, 95% CI [-0.79, 4.27], t(151) = 1.35, p = 0.177; Std. beta = 0.24, 95% CI [-0.11, 0.58])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

nb_mcs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict nb_mcs with group and time_point (formula: nb_mcs ~ 1 + group + time_point + group * time_point). The model included login_id as random effect (formula: ~1 | login_id). The model’s total explanatory power is substantial (conditional R2 = 0.60) and the part related to the fixed effects alone (marginal R2) is of 2.50e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 50.86 (95% CI [48.62, 53.10], t(151) = 44.49, p < .001). Within this model:

• The effect of group [treatment] is statistically non-significant and positive (beta = 0.62, 95% CI [-2.74, 3.98], t(151) = 0.36, p = 0.717; Std. beta = 0.08, 95% CI [-0.34, 0.49])
• The effect of time point [2nd] is statistically non-significant and negative (beta = -0.41, 95% CI [-2.77, 1.95], t(151) = -0.34, p = 0.732; Std. beta = -0.05, 95% CI [-0.34, 0.24])
• The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.33, 95% CI [-3.07, 3.72], t(151) = 0.19, p = 0.851; Std. beta = 0.04, 95% CI [-0.38, 0.46])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Table